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asrigordonLv1
15 Oct 2022
Based on the sample histogram above, would you be comfortable using the Central Limit Theorem?
◯ Not sure. We cannot tell the value of n, but the sample histogram suggests that the population is not normally distributed
◯ No, n<30 and the skewed sample histogram suggests that the population is not normally distributed
◯ Yes, n>30 so the shape of the population distribution does not matter
◯ Yes, n<30 but the symmetric sample histogram suggests that the population is normally distributed
Based on the sample histogram above, would you be comfortable using the Central Limit Theorem?
◯ Yes, n<30 but the symmetric sample histogram suggests that the population is normally distributed
◯ Not sure. We cannot tell the value of n, but the sample histogram suggests that the population is not normally distributed
◯ Yes, n>30 so the shape of the population distribution does not matter
◯ No, n<30 and the skewed sample histogram suggests that the population is not normally distributed
Based on the sample histogram above, would you be comfortable using the Central Limit Theorem?
◯ Not sure. We cannot tell the value of n, but the sample histogram suggests that the population is not normally distributed
◯ No, n<30 and the skewed sample histogram suggests that the population is not normally distributed
◯ Yes, n>30 so the shape of the population distribution does not matter
◯ Yes, n<30 but the symmetric sample histogram suggests that the population is normally distributed
Based on the sample histogram above, would you be comfortable using the Central Limit Theorem?
◯ Yes, n<30 but the symmetric sample histogram suggests that the population is normally distributed
◯ Not sure. We cannot tell the value of n, but the sample histogram suggests that the population is not normally distributed
◯ Yes, n>30 so the shape of the population distribution does not matter
◯ No, n<30 and the skewed sample histogram suggests that the population is not normally distributed
kibettitus2020Lv10
7 Nov 2022